Developing educational resources for population genetics in R: an open and collaborative approach

Zhian N. Kamvar, Margarita M. López-Uribe, Simone Coughlan, Niklaus J. Grünwald, Hilmar Lapp, Stéphanie Manel

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


The r computing and statistical language community has developed a myriad of resources for conducting population genetic analyses. However, resources for learning how to carry out population genetic analyses in r are scattered and often incomplete, which can make acquiring this skill unnecessarily difficult and time consuming. To address this gap, we developed an online community resource with guidance and working demonstrations for conducting population genetic analyses in r. The resource is freely available at and includes material for both novices and advanced users of r for population genetics. To facilitate continued maintenance and growth of this resource, we developed a toolchain, process and conventions designed to (i) minimize financial and labour costs of upkeep; (ii) to provide a low barrier to contribution; and (iii) to ensure strong quality assurance. The toolchain includes automatic integration testing of every change and rebuilding of the website when new vignettes or edits are accepted. The process and conventions largely follow a common, distributed version control-based contribution workflow, which is used to provide and manage open peer review by designated website editors. The online resources include detailed documentation of this process, including video tutorials. We invite the community of population geneticists working in r to contribute to this resource, whether for a new use case of their own, or as one of the vignettes from the ‘wish list’ we maintain, or by improving existing vignettes.

Original languageEnglish (US)
Pages (from-to)120-128
Number of pages9
JournalMolecular Ecology Resources
Issue number1
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Ecology, Evolution, Behavior and Systematics
  • Genetics


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